VeRL-Omni v0.3.0 released with async training and broader multimodal post-training

VeRL-Omni v0.3.0 was released with asynchronous and decoupled RL execution paths, the V1 trainer as the default, and expanded post-training coverage across image, video, audio, and multimodal understanding. The release adds fully async Qwen3-Omni text and audio training, separate-async Omni and diffusion training with a replay buffer, and new recipes including MiniMax H3 with DiffusionNFT and MiniCPM-o 4.5 GSPO. In a MiniCPM-o 4.5 AVQA experiment on 4×H800 80 GB, separate-async 3+1 was about 9% slower per prompt than colocated 4+0 at natural response length, roughly tied at 512 tokens, and about 6.7% faster at 1024 tokens.